## Introduction

This article describes how to go from a standard table in Displayr showing no significant differences:

To a table that shows cell comparison significant differences:

## Method

To perform significance testing in Q:

- From the toolbar, from the
**Show Significance**menu, select one of the following options:

You can select**Arrows and Font Colors,**or you can select**Arrows**OR**Font colors**individually if you instead prefer to show one or the other. These will conduct*exception tests,*also called*complement tests*, where the value in a cell is tested against the value of respondents*not*in that column, or its*exception*. You can also select**Compare columns**to perform*column comparisons,*also called*pairwise testing*.

### Using the New Statistical Assumptions dialog:

Beginning in Q15.14.1.0, a new Statistical Assumptions dialog has been added that is designed to give you complete control over statistical testing.

- Right-click the table and select
**Table Options > Statistics Assumptions**. If you want to change the statistical assumptions for your entire project, from the toolbar, select**Edit > Project Options > Customize > Statistical Assumptions**You will see the Statistical Assumptions dialog: - Select from one of the four tabs on the top depending on the type of task you want to perform:
**Significance Levels**:**Show significance**: show higher or lower significance with arrows, font colors (tables only), or using symbols to show significant differences between columns**Overall significance level**: is used when determining which results to show as being statistically significant**Minimal sample size for testing**: where cells have sample sizes of less no significance test is conducted when conducting automated tests of statistical significance between cells (i.e., Cell Comparisons and Column Comparisons).**Extra deff**: by default, the deff value (design effect) is set to 1.00**Significance levels and appearance:**symbols used to denote different levels of statistical significance.

**Test Type:****Proportions**: non-parametric tests will be done on categorical data**Means**: t-test will be done on numeric data and corrected with Bessel’s correction**Correlations**: default is Pearson**Equal variance in tests when sample size is less than**: if the sample size is less than 10 variance is assumed equal.

**Exceptions Test**:**Multiple comparison correction**: False Discovery Rate is by default applied to help reduce the number of false positives based on the entire table. A check box is available if instead, you prefer to apply the correction within each span within each row.

**Column Comparisons:****Multiple Comparison correction**: the following corrections are available for post hoc testing: Fisher LSD, Duncan, Newman Keuls (S-N-K), Tukey HSD, False Discovery Rate (FDR), False Discovery Rate (pooled t-test), Bonferroni, Bonferroni (pooled t-test), Dunnett.**Overlaps**: The default is to ignore the sample that overlaps between columns when respondents in columns are not mutually exclusive**No test symbol**: - is shown if a test isn’t performed due to settings**Symbol for non-significant test**: nothing is shown if a test comes back insignificant**A****NOVA-Type Test**: Select whether ANOVA-type tests are run as part of the testing**Show redundant tests**: Select whether to show significance on one cell (the one with the higher value) or all cells involved in testing.**Show as groups**: Show letters for insignificant columns rather than significant**Recycle column letters**: Each span begins labeling columns at A

### Restore all of the fields to their default values

- Click the
**Restore**button

## Next

How to Modify Significance Tests

How To Override Default Statistical Testing Settings

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